Making the best of a bad situation Using side effects to reveal new targets for old drugs Lars Juhl Jensen EMBL Heidelberg

the problem

two drugs

do they share a target?

chemical similarity

Tanimoto coefficients

similar drugs share targets

only trivial predictions

the idea

chemical perturbations

phenotypic readout

drug treatment

side effects

the implementation

information on side effects

package inserts

text mining

side-effect ontology

backtracking

side-effect correlations

GSC weighting

side-effect frequencies

raw similarity score

p-values

side-effect similarity

chemical similarity

reference set

drug–target pairs

drug–drug pairs

score bins

benchmark

fit calibration function

probabilistic scores

the results

drug–drug network

categorization

map onto score space

the experiments

20 drug–drug relations

in vitro binding assays

K i <10 µM for 11 of 20

cell assays

9 of 9 showed activity

the future

drug–target relations

Acknowledgments Monica Campillos Michael Kuhn Anne-Claude Gavin Peer Bork

Monica Campillos

Michael Kuhn

Anne-Claude Gavin

Peer Bork

http://larsjuhljensen.wordpress.com